A New Compression Scheme Based on Adaptive Vector Quantization and Singular Value Decomposition

2016 ◽  
Vol 11 (5) ◽  
pp. 445 ◽  
Author(s):  
Imene Soussi ◽  
Mohamed Ouslim
Keyword(s):  
Singular Value Decomposition ◽  
Vector Quantization ◽  
Singular Value ◽  
Compression Scheme ◽  
Adaptive Vector Quantization ◽  
Value Decomposition

scholarly journals Adaptive vector quantization in SVD MIMO system backward link with limited number of active sub channels

2004 ◽  
Vol 1 (3) ◽  
pp. 113-123
Author(s):  
Predrag Ivanis ◽  
Dusan Drajic
Keyword(s):  
Singular Value Decomposition ◽  
Vector Quantization ◽  
Bit Error Rate ◽  
Error Rate ◽  
Mimo Systems ◽  
Mimo System ◽  
Singular Value ◽  
Lbg Algorithm ◽  
Adaptive Vector Quantization ◽  
Value Decomposition

This paper presents combination of Channel Optimized Vector Quantization based on LBG algorithm and sub channel power allocation for MIMO systems with Singular Value Decomposition and limited number of active sub channels. Proposed algorithm is designed to enable maximal throughput with bit error rate bellow some tar- get level in case of backward channel capacity limitation. Presence of errors effect in backward channel is also considered.

Color Image Compression Using Block Singular Value Decomposition

2013 ◽  
Vol 303-306 ◽  
pp. 2122-2125
Author(s):  
Peng Fei Xu ◽  
Hong Bin Zhang ◽  
Xin Feng Wang ◽  
Zheng Yong Yu
Keyword(s):  
Singular Value Decomposition ◽  
Image Compression ◽  
Basic Principle ◽  
Color Image ◽  
Singular Value ◽  
Matrix Structure ◽  
Compression Scheme ◽  
The Matrix ◽  
Value Decomposition ◽  
Color Image Compression

This paper looks at the application of Singular Value Decomposition (SVD) to color image compression. Based on the basic principle and characteristics of SVD, combined with the image of the matrix structure. A block SVD-based image compression scheme is demonstrated and the usage feasibility of Block SVD-based image compression is proved.

scholarly journals A discrete wavelet transform-singular value decomposition system for image coding

2007 ◽  
Vol 5 (02) ◽  
Author(s):  
H. de Jesús Ochoa-Domí­nguez ◽  
K. R. Rao
Keyword(s):  
Wavelet Transform ◽  
Singular Value Decomposition ◽  
Vector Quantization ◽  
Image Coding ◽  
Decision Criterion ◽  
Singular Value ◽  
Discrete Wavelet ◽  
Scalar Quantization ◽  
Value Decomposition ◽  
Decomposition System

A system that combines techniques of wavelet transform (DWT) and singular value decomposition (SVD) to encode images is presented. The image is divided into tiles or blocks of 64x64 pixels. The decision criterion as to which transform to use is based on the standard deviation of the 8x8 pixel subblocks of the tile to encode. A successive approximation quantizer is used to encode the subbands and vector quantization/scalar quantization is used to encode the SVD eigenvectors/eigenvalues, respectively. For coding color images, the RGB components are transformed into YCbCr before encoding in 4:2:0 format. Results show that the proposed system outperforms the JPEG and approaches the JPEG2000.

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